A chargeback application may be used to account for operational costs involved in providing and maintaining an information technology (IT) infrastructure, including the cost for IT services and applications. Measuring resource utilization and calculating the corresponding IT operational cost enable a data center to account for IT resource utilized, bill for the IT services provided and meet target return on investments (ROIs).
In a non-virtualized environment, a physical server and the associated resources like applications running on the physical server can be easily mapped to a department using them and billing them for such resource utilizations. Also, costs associated with maintenance and licensing can be directly associated to a department, thereby enabling the data center to calculate the IT operational costs.
However, in a rapidly growing and changing IT infrastructure, such as a cloud infrastructure, there may be significant uncertainty of customer base, rapidly changing requirements, frequent changes in capital expenditure (CAPEX) and operating expenditure (OPEX). Further, there may be lack of visibility to future trending and risks and frequent and future purchases of capacity. In such an environment, accounting for IT resource utilization, achieving yearly targets and meeting target ROIs can be a significant challenge. Furthermore the task of determining IT operational costs in a virtualized environment, which typically includes multiple physical computing systems that each include a hypervisor, virtual machine (VM) monitor, or similar logic that is configured to manage concurrent execution of multiple virtual machines (VMs) that may be shared across different business entities, can be even more challenging.
As a result, accounting for IT resource utilization, achieving yearly targets and meeting target ROIs may be significantly difficult. The difficulty in accounting for the IT resource utilization gets further compounded when applications and services get shifted over time to different physical servers based on load and available infrastructure resources. Furthermore, computing unit resource usage in such an environment can be difficult and challenging.